上海交通大学学报

上海交通大学学报

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数据中心接入下应对地震灾害的能源站弹性提升规划方法

  

  1. 上海交通大学 电力传输与功率变换控制教育部重点实验室，上海 200240
  • 通讯作者: 张沈习，副研究员，博士生导师；E-mail：willzsx@sjtu.edu.cn
  • 作者简介:金文广（2000-），硕士生，从事综合能源系统规划研究。
  • 基金资助:

    国家自然科学基金项目(52177099)，上海青年科技启明星计划项目(23QA1405400)

Resilience Enhancement Planning Method of Energy Station in Response to Earthquake Disaster with Data Center Access

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  1. Key Laboratory of Control of Power Transmission and Transformation of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China

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摘要： 近年来，地震灾害等极端自然事件频发，导致综合能源系统元件故障概率大幅提高，严重影响了综合能源系统的安全可靠运行。文中针对互联多能源站，提出一种数据中心接入下应对地震灾害的多能源站弹性提升规划模型。首先，对地震灾害下能源站故障进行建模，并分析计及数据中心响应的能源站弹性提升潜力。然后，以年综合成本最小为目标函数，以数据中心服务质量、地震灾害后多能源站异质能源切负荷上限等为约束条件，构建数据中心接入下应对地震灾害的能源站弹性提升规划模型。最后，设置多个场景进行对比分析，并基于某改进实际算例验证所提规划方法的有效性。

关键词:

"> 地震灾害；能源站规划；数据中心；数据负载时空调节；余热回收；弹性

Abstract:

In recent years, frequent occurrences of extreme natural events such as earthquakes have led to a significant increase in the probability of component failures within integrated energy systems, severely impacting their safe and reliable operation. This article addresses the interconnected multiple energy stations under the context of data centers’ accession, proposing a planning model for enhancing the resilience of such stations in response to earthquake disasters. Firstly, the model establishes a representation of energy station failures during earthquakes and conducts an analysis of the potential for resilience enhancement considering the response of the data center. Subsequently, with the objective function of minimizing the annual comprehensive cost, the planning model is formulated subject to constraints encompassing data center service quality and heterogeneous energy curtailment strategies among the multiple energy stations under earthquake disturbances. Finally, the proposed planning method is validated through comparative analysis across multiple scenarios and an examination of an improved practical case study, substantiating its effectiveness.

Key words: earthquake disaster, energy stations planning, data centers; spatio-temporal regulation of workloads, waste heat reuse, resilience

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